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Rapid uncertainty propagation and chance‐constrained path planning for small unmanned aerial vehicles
Author(s) -
Berning Andrew W.,
Girard Anouck,
Kolmanovsky Ilya,
D'Souza Sarah N.
Publication year - 2020
Publication title -
advanced control for applications: engineering and industrial systems
Language(s) - English
Resource type - Journals
ISSN - 2578-0727
DOI - 10.1002/adc2.23
Subject(s) - national airspace system , motion planning , path (computing) , trajectory , fixed wing , computer science , covariance , aviation , mathematical optimization , air traffic control , quadratic equation , real time computing , aerospace engineering , engineering , mathematics , artificial intelligence , wing , robot , statistics , physics , geometry , astronomy , programming language
Abstract With the number of small unmanned aircraft systems in the national airspace projected to increase in the next few years, there is growing interest in a traffic management system capable of handling the demands of this aviation sector. It is expected that such a system will involve trajectory prediction, uncertainty propagation, and path planning algorithms. In this work, we use linear covariance propagation in combination with a quadratic programming‐based collision detection algorithm to rapidly validate declared flight plans. Additionally, these algorithms are combined with a dynamic informed RRT ∗ algorithm, resulting in a computationally efficient algorithm for chance‐constrained path planning. Detailed numerical examples for both fixed‐wing and quadrotor small unmanned aircraft system models are presented.